Statistical optimization of process variables for the large-scale production of Metarhizium anisopliae conidiospores in solid-state fermentation

Optimization of conidial production was achieved by response surface methodology (RSM), a powerful mathematical approach widely applied in the optimization of fermentation process, using the three substrates; rice, barley and sorghum at variable pH, moisture content and yeast extract concentrations....

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Veröffentlicht in:Bioresource technology 2008-04, Vol.99 (6), p.1530-1537
Hauptverfasser: Bhanu Prakash, G.V.S., Padmaja, V., Siva Kiran, R.R.
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Sprache:eng
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Zusammenfassung:Optimization of conidial production was achieved by response surface methodology (RSM), a powerful mathematical approach widely applied in the optimization of fermentation process, using the three substrates; rice, barley and sorghum at variable pH, moisture content and yeast extract concentrations. These three factors were found to be important, affecting Metarhizium anisopliae spore production. A 2 3 full factorial central composite design and RSM were applied to determine the optimal concentration of each variable. A second-order polynomial was determined by the multiple regression analysis of the experimental data. Moisture content of 75.68% for sorghum, 73.21% for barley and 22.34% for rice produced optimal results. Maximal conidial yield was recorded for rice at a pH of 7.01; at 7.06 for sorghum and at 6.76 for barley.
ISSN:0960-8524
1873-2976
DOI:10.1016/j.biortech.2007.04.031